Behind the Scenes with Urge's and Napster's Recommendation Engine

I've written in the past about Urge's new recommendation engine, which they're calling "My Auto-Mix," and which I'm quite a big fan of. I spoke on the phone today with Michael Papish, the president and CEO of MediaUnbound, the company that licenses the recommendation technology to companies like Urge and Napster. He gave me kind of a behind-the-scenes tour of how the technology works.
Urge's My Auto-Mix feature uses three sliders which you can adjust to tweak the freshness (how new the music is), popularity (how many people like the music), and familiarity (how likely you are to know the tune, based on your catalog). Adjusting the various sliders can either bring up a list of classic tunes you're likely to know and enjoy, or newer or undiscovered stuff that you're probably hearing for the first time.

Want to further customize your returns? You can also create playlists using the aforementioned sliders along with a mood bar, which runs the gamut from Malevolent to Ethereal, with scads of in-betweens like Brooding, Cathartic, or Trippy.

Anyway, that's all rehash--you can learn more about the service here. My chat with Mr. Papish was about the specifics of the service, which uses a human-computer hybrid model that combines the best qualities of both.
As Papish says: "Computer algorithms don't know anything about music." Computers can look for patterns, but they miss obvious things sometimes. They're great for determining things like tempo, keys, and non-subjective sound qualities, but ask a computer to build a list of 30 sad songs and it will have a tough time, unless you pre-programmed it to define "sad" as slow and in a minor key. By that definition then, the slower a song is, the "sadder" it is, which may or may not be true (I'm oversimplifying, sorry!).

Humans, on the other hand, just don't "scale" well, according to Papish. Meaning you can't really hand a team of humans a 2-million song library and expect to be able to launch a service based on their collected data. Papish says his team of humans do the uniquely human tasks, like building genre maps and selecting "sad" songs and so on. Unlike a computer, you can ask the team to pick 30 country songs that are really sad and they can come back with meaningful results.

MediaUnbound also has some advantages that other recommendation engines like Pandora don't. Specifically, MediaUnbound takes your Urge or Napster catalog into account when making recommendations.

"We want to know more than what the listener listens to," said Papish. "We want to know who the listener is. Are they experimental? Do they like popular music? Older music?" MediaUnbound essentially builds a musical profile for you, and takes it into account as you use the sliders to get a custom fit. So you can pick a mood and position for all the sliders, but if I pick the same mood and the same slider settings, my list won't come out the same as yours.

Another advantage of partnering with Urge and Napster is the fact that users can download the playlist's recommended music for free, so there's no risk in exploring new music. "With a subscription service, we can stretch the boundaries a bit with recommendations," Papish told me. "Music is free, so listeners are willing take more risks. You should be getting things you haven't heard before."

And, of course, if the thought of new music scares you, just crank up the Popularity and Familiarity to get back to the comfortable.

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